Higher Urinary Sodium, a Proxy for Intake, Is Associated with Increased Calcium Excretion and Lower Hip Bone Density in Healthy Young Women with Lower Calcium Intakes
Bibliographic record
Abstract
We assessed 24-h urinary sodium (Na) and its relationship with urinary calcium (Ca) and areal bone mineral density (aBMD) at the whole body, lumbar spine and total hip in a cross-sectional study. 102 healthy non-obese women completed timed 24-h urine collections which were analyzed for Na and Ca. Dietary intakes were estimated using a validated food frequency questionnaire. Participants were grouped as those with lower vs. higher calcium intake by median split (506 mg/1000 kcal). Dietary Na intake correlated with 24-h urinary loss. Urinary Na correlated positively with urinary Ca for all participants (r = 0.29, p < 0.01) and among those with lower (r = 0.37, p < 0.01) but not higher calcium intakes (r = 0.19, p = 0.19). Urinary Na was inversely associated with hip aBMD for all participants (r = -0.21, p = 0.04) and among women with lower (r = -0.36, p < 0.01) but not higher (r = -0.05, p = 0.71) calcium intakes. Urinary Na also entered a regression equation for hip aBMD in women with lower Ca intakes, contributing 5.9% to explained variance. In conclusion, 24-h urinary Na (a proxy for intake) is associated with higher urinary Ca loss in young women and may affect aBMD, particularly in those with lower calcium intakes.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".